Overview

Brought to you by YData

Dataset statistics

Number of variables18
Number of observations103770
Missing cells85
Missing cells (%)< 0.1%
Duplicate rows643
Duplicate rows (%)0.6%
Total size in memory14.3 MiB
Average record size in memory144.0 B

Variable types

Text3
Numeric12
Categorical2
DateTime1

Alerts

Dataset has 643 (0.6%) duplicate rowsDuplicates
Topic_4 is highly overall correlated with breadth and 1 other fieldsHigh correlation
breadth is highly overall correlated with Topic_4High correlation
depth is highly overall correlated with Topic_4High correlation
has_images is highly imbalanced (76.4%) Imbalance
Helpfulness is highly skewed (γ1 = 102.1419687) Skewed
Helpfulness has 93849 (90.4%) zeros Zeros

Reproduction

Analysis started2025-01-14 13:53:47.473425
Analysis finished2025-01-14 13:54:08.351408
Duration20.88 seconds
Software versionydata-profiling vv4.12.1
Download configurationconfig.json

Variables

Distinct77
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size810.8 KiB
2025-01-14T22:54:08.576854image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/

Length

Max length199
Median length166
Mean length134.51351
Min length37

Characters and Unicode

Total characters13958467
Distinct characters79
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowPanasonic Portable AM / FM Radio, Battery Operated Analog Radio, AC Powered, Silver (RF-2400D) 22.8 x 7.8 x 10.8
2nd rowPanasonic Portable AM / FM Radio, Battery Operated Analog Radio, AC Powered, Silver (RF-2400D) 22.8 x 7.8 x 10.8
3rd rowPanasonic Portable AM / FM Radio, Battery Operated Analog Radio, AC Powered, Silver (RF-2400D) 22.8 x 7.8 x 10.8
4th rowPanasonic Portable AM / FM Radio, Battery Operated Analog Radio, AC Powered, Silver (RF-2400D) 22.8 x 7.8 x 10.8
5th rowPanasonic Portable AM / FM Radio, Battery Operated Analog Radio, AC Powered, Silver (RF-2400D) 22.8 x 7.8 x 10.8
ValueCountFrequency (%)
81554
 
3.6%
with 58679
 
2.6%
for 49353
 
2.2%
to 42082
 
1.9%
and 41908
 
1.9%
tv 32437
 
1.4%
wireless 28415
 
1.3%
black 25724
 
1.1%
ipad 22283
 
1.0%
mount 20897
 
0.9%
Other values (692) 1847217
82.1%
2025-01-14T22:54:08.946076image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2146779
 
15.4%
e 947819
 
6.8%
o 748745
 
5.4%
a 717288
 
5.1%
t 704941
 
5.1%
i 672044
 
4.8%
r 612767
 
4.4%
n 521444
 
3.7%
l 474610
 
3.4%
s 399488
 
2.9%
Other values (69) 6012542
43.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 13958467
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
2146779
 
15.4%
e 947819
 
6.8%
o 748745
 
5.4%
a 717288
 
5.1%
t 704941
 
5.1%
i 672044
 
4.8%
r 612767
 
4.4%
n 521444
 
3.7%
l 474610
 
3.4%
s 399488
 
2.9%
Other values (69) 6012542
43.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 13958467
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
2146779
 
15.4%
e 947819
 
6.8%
o 748745
 
5.4%
a 717288
 
5.1%
t 704941
 
5.1%
i 672044
 
4.8%
r 612767
 
4.4%
n 521444
 
3.7%
l 474610
 
3.4%
s 399488
 
2.9%
Other values (69) 6012542
43.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 13958467
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
2146779
 
15.4%
e 947819
 
6.8%
o 748745
 
5.4%
a 717288
 
5.1%
t 704941
 
5.1%
i 672044
 
4.8%
r 612767
 
4.4%
n 521444
 
3.7%
l 474610
 
3.4%
s 399488
 
2.9%
Other values (69) 6012542
43.1%

Average_rating
Real number (ℝ)

Distinct12
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.5065973
Minimum3.8
Maximum4.9
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size810.8 KiB
2025-01-14T22:54:09.041639image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/

Quantile statistics

Minimum3.8
5-th percentile3.9
Q14.4
median4.6
Q34.7
95-th percentile4.8
Maximum4.9
Range1.1
Interquartile range (IQR)0.3

Descriptive statistics

Standard deviation0.23024045
Coefficient of variation (CV)0.051089643
Kurtosis1.1738643
Mean4.5065973
Median Absolute Deviation (MAD)0.1
Skewness-1.2286948
Sum467649.6
Variance0.053010663
MonotonicityNot monotonic
2025-01-14T22:54:09.117982image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
4.6 30121
29.0%
4.7 23364
22.5%
4.5 13851
13.3%
4.3 12024
 
11.6%
4.4 6496
 
6.3%
4.8 4876
 
4.7%
3.9 3329
 
3.2%
4.1 2913
 
2.8%
4.2 2695
 
2.6%
3.8 1881
 
1.8%
Other values (2) 2220
 
2.1%
ValueCountFrequency (%)
3.8 1881
 
1.8%
3.9 3329
 
3.2%
4 1121
 
1.1%
4.1 2913
 
2.8%
4.2 2695
 
2.6%
4.3 12024
 
11.6%
4.4 6496
 
6.3%
4.5 13851
13.3%
4.6 30121
29.0%
4.7 23364
22.5%
ValueCountFrequency (%)
4.9 1099
 
1.1%
4.8 4876
 
4.7%
4.7 23364
22.5%
4.6 30121
29.0%
4.5 13851
13.3%
4.4 6496
 
6.3%
4.3 12024
 
11.6%
4.2 2695
 
2.6%
4.1 2913
 
2.8%
4 1121
 
1.1%

Num_of_Rating
Real number (ℝ)

Distinct77
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean50352.655
Minimum15398
Maximum223181
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size810.8 KiB
2025-01-14T22:54:09.221442image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/

Quantile statistics

Minimum15398
5-th percentile16453
Q121988
median36537
Q362436
95-th percentile122681
Maximum223181
Range207783
Interquartile range (IQR)40448

Descriptive statistics

Standard deviation40873.233
Coefficient of variation (CV)0.81173938
Kurtosis5.0957856
Mean50352.655
Median Absolute Deviation (MAD)16550
Skewness2.115707
Sum5.225095 × 109
Variance1.6706212 × 109
MonotonicityNot monotonic
2025-01-14T22:54:09.322956image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
110444 1983
 
1.9%
33336 1954
 
1.9%
76290 1881
 
1.8%
104579 1780
 
1.7%
33087 1666
 
1.6%
24205 1656
 
1.6%
119789 1635
 
1.6%
18908 1607
 
1.5%
64529 1588
 
1.5%
201075 1586
 
1.5%
Other values (67) 86434
83.3%
ValueCountFrequency (%)
15398 1040
1.0%
15469 1088
1.0%
16023 1190
1.1%
16085 1452
1.4%
16453 1121
1.1%
17206 1449
1.4%
17230 1034
1.0%
17318 1099
1.1%
18061 1018
1.0%
18244 1407
1.4%
ValueCountFrequency (%)
223181 1385
1.3%
201075 1586
1.5%
148591 1147
1.1%
122681 1327
1.3%
119789 1635
1.6%
110468 1346
1.3%
110444 1983
1.9%
104579 1780
1.7%
100244 1555
1.5%
85201 1019
1.0%

Rating
Categorical

Distinct5
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size810.8 KiB
5.0
70640 
1.0
12668 
4.0
9621 
3.0
 
6027
2.0
 
4814

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters311310
Distinct characters7
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row5.0
2nd row1.0
3rd row3.0
4th row5.0
5th row1.0

Common Values

ValueCountFrequency (%)
5.0 70640
68.1%
1.0 12668
 
12.2%
4.0 9621
 
9.3%
3.0 6027
 
5.8%
2.0 4814
 
4.6%

Length

2025-01-14T22:54:09.409317image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-01-14T22:54:09.504944image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
ValueCountFrequency (%)
5.0 70640
68.1%
1.0 12668
 
12.2%
4.0 9621
 
9.3%
3.0 6027
 
5.8%
2.0 4814
 
4.6%

Most occurring characters

ValueCountFrequency (%)
. 103770
33.3%
0 103770
33.3%
5 70640
22.7%
1 12668
 
4.1%
4 9621
 
3.1%
3 6027
 
1.9%
2 4814
 
1.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 311310
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
. 103770
33.3%
0 103770
33.3%
5 70640
22.7%
1 12668
 
4.1%
4 9621
 
3.1%
3 6027
 
1.9%
2 4814
 
1.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 311310
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
. 103770
33.3%
0 103770
33.3%
5 70640
22.7%
1 12668
 
4.1%
4 9621
 
3.1%
3 6027
 
1.9%
2 4814
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 311310
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
. 103770
33.3%
0 103770
33.3%
5 70640
22.7%
1 12668
 
4.1%
4 9621
 
3.1%
3 6027
 
1.9%
2 4814
 
1.5%
Distinct66230
Distinct (%)63.8%
Missing40
Missing (%)< 0.1%
Memory size810.8 KiB
2025-01-14T22:54:09.798479image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/

Length

Max length100
Median length87
Mean length21.959163
Min length1

Characters and Unicode

Total characters2277824
Distinct characters300
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique60339 ?
Unique (%)58.2%

Sample

1st rowIt's a good product
2nd rownothing came in?
3rd rowGreat for basement or garage use.
4th rowPROS/CONS Good things come in SMALL packages!
5th rowDoesn’t pick up well
ValueCountFrequency (%)
great 18225
 
4.4%
good 10292
 
2.5%
for 9811
 
2.4%
works 9531
 
2.3%
the 9249
 
2.3%
it 7947
 
1.9%
to 7713
 
1.9%
and 6667
 
1.6%
a 6348
 
1.5%
not 6262
 
1.5%
Other values (13646) 318906
77.6%
2025-01-14T22:54:10.329434image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
308547
 
13.5%
e 217866
 
9.6%
t 166996
 
7.3%
o 164346
 
7.2%
r 130583
 
5.7%
a 130203
 
5.7%
s 106882
 
4.7%
i 98331
 
4.3%
n 91260
 
4.0%
d 77341
 
3.4%
Other values (290) 785469
34.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 2277824
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
308547
 
13.5%
e 217866
 
9.6%
t 166996
 
7.3%
o 164346
 
7.2%
r 130583
 
5.7%
a 130203
 
5.7%
s 106882
 
4.7%
i 98331
 
4.3%
n 91260
 
4.0%
d 77341
 
3.4%
Other values (290) 785469
34.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 2277824
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
308547
 
13.5%
e 217866
 
9.6%
t 166996
 
7.3%
o 164346
 
7.2%
r 130583
 
5.7%
a 130203
 
5.7%
s 106882
 
4.7%
i 98331
 
4.3%
n 91260
 
4.0%
d 77341
 
3.4%
Other values (290) 785469
34.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 2277824
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
308547
 
13.5%
e 217866
 
9.6%
t 166996
 
7.3%
o 164346
 
7.2%
r 130583
 
5.7%
a 130203
 
5.7%
s 106882
 
4.7%
i 98331
 
4.3%
n 91260
 
4.0%
d 77341
 
3.4%
Other values (290) 785469
34.5%
Distinct95985
Distinct (%)92.5%
Missing45
Missing (%)< 0.1%
Memory size810.8 KiB
2025-01-14T22:54:10.657843image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/

Length

Max length6427
Median length2243
Mean length169.6506
Min length1

Characters and Unicode

Total characters17597008
Distinct characters410
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique94179 ?
Unique (%)90.8%

Sample

1st rowThis radio was perfect for my father. He's older (in his 80s) and he wanted a simple transistor radio for the bathroom that runs on batteries. He didn't want anything too fancy or expensive. This fits the bill.
2nd rowI couldn't get any stations in , worthless to me. YouTube videos why I bought it{: buyer beware!
3rd rowThis affordable radio is perfect for my needs. Yet, I miss the quality from the higher end Sony portable. Sorry, the sound is a bit tinny. Yet, I am a fan of the controls, display and design. Good value.
4th rowPROS and CONS and why I chose this one. The story:My mother still lives in independent living with her older sister (she's turning 90, her sister 92).She couldn't get visitors for her birthday because all independent and assisted living places are on lockdown with what's going on.SO I had to find something EASY for her to set up on her own, that was small for her bedside table, and would be a good-sounding radio. EUREKA!PROS:PACKAGING - I was concerned re how it would arrive, but my mother said it was in heavy foam packaging. Came in perfect condition.SIZE - PERFECT SMALL RADIO for her night stand. MUCH smaller than the 22 inch dimensions it shows in top description! It's small enough for a SMALL nightstand.SET UP - MY mother had no problem setting it up or figuring out knobs. This is as easy as radios from the '60's. Basically a couple knobs and a switch to go back and forth between AM and FMSOUND - I was on the phone with my mother as she dialed through various stations and GREAT sound. She was delighted and said, HEAR THIS!PRICE - CAN'T BEAT THE PRICE!
5th rowWaste of money,,,,, can’t get stations on this radio as clear as others
ValueCountFrequency (%)
the 147292
 
4.5%
i 100446
 
3.1%
to 97877
 
3.0%
and 92966
 
2.8%
it 85647
 
2.6%
a 76133
 
2.3%
for 50965
 
1.6%
this 50603
 
1.5%
is 49177
 
1.5%
my 48342
 
1.5%
Other values (58146) 2488344
75.7%
2025-01-14T22:54:11.088371image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3228633
18.3%
e 1601899
 
9.1%
t 1323642
 
7.5%
o 1101109
 
6.3%
a 1002576
 
5.7%
s 863998
 
4.9%
i 859949
 
4.9%
n 830358
 
4.7%
r 767806
 
4.4%
h 638044
 
3.6%
Other values (400) 5378994
30.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 17597008
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
3228633
18.3%
e 1601899
 
9.1%
t 1323642
 
7.5%
o 1101109
 
6.3%
a 1002576
 
5.7%
s 863998
 
4.9%
i 859949
 
4.9%
n 830358
 
4.7%
r 767806
 
4.4%
h 638044
 
3.6%
Other values (400) 5378994
30.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 17597008
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
3228633
18.3%
e 1601899
 
9.1%
t 1323642
 
7.5%
o 1101109
 
6.3%
a 1002576
 
5.7%
s 863998
 
4.9%
i 859949
 
4.9%
n 830358
 
4.7%
r 767806
 
4.4%
h 638044
 
3.6%
Other values (400) 5378994
30.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 17597008
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
3228633
18.3%
e 1601899
 
9.1%
t 1323642
 
7.5%
o 1101109
 
6.3%
a 1002576
 
5.7%
s 863998
 
4.9%
i 859949
 
4.9%
n 830358
 
4.7%
r 767806
 
4.4%
h 638044
 
3.6%
Other values (400) 5378994
30.6%
Distinct1311
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size810.8 KiB
Minimum2020-01-01 00:00:00
Maximum2023-08-25 00:00:00
Invalid dates0
Invalid dates (%)0.0%
2025-01-14T22:54:11.202542image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
2025-01-14T22:54:11.309139image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

Helpfulness
Real number (ℝ)

Skewed  Zeros 

Distinct66
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.21728823
Minimum0
Maximum589
Zeros93849
Zeros (%)90.4%
Negative0
Negative (%)0.0%
Memory size810.8 KiB
2025-01-14T22:54:11.407564image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum589
Range589
Interquartile range (IQR)0

Descriptive statistics

Standard deviation3.0207622
Coefficient of variation (CV)13.902098
Kurtosis15962.643
Mean0.21728823
Median Absolute Deviation (MAD)0
Skewness102.14197
Sum22548
Variance9.1250044
MonotonicityNot monotonic
2025-01-14T22:54:11.506254image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 93849
90.4%
1 7206
 
6.9%
2 1311
 
1.3%
3 477
 
0.5%
4 264
 
0.3%
5 161
 
0.2%
6 92
 
0.1%
7 81
 
0.1%
8 50
 
< 0.1%
9 37
 
< 0.1%
Other values (56) 242
 
0.2%
ValueCountFrequency (%)
0 93849
90.4%
1 7206
 
6.9%
2 1311
 
1.3%
3 477
 
0.5%
4 264
 
0.3%
5 161
 
0.2%
6 92
 
0.1%
7 81
 
0.1%
8 50
 
< 0.1%
9 37
 
< 0.1%
ValueCountFrequency (%)
589 1
< 0.1%
283 1
< 0.1%
243 1
< 0.1%
235 1
< 0.1%
189 1
< 0.1%
174 1
< 0.1%
136 1
< 0.1%
132 1
< 0.1%
118 1
< 0.1%
117 1
< 0.1%

has_images
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size810.8 KiB
0
99770 
1
 
4000

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters103770
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 99770
96.1%
1 4000
 
3.9%

Length

2025-01-14T22:54:11.606078image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-01-14T22:54:11.689554image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
ValueCountFrequency (%)
0 99770
96.1%
1 4000
 
3.9%

Most occurring characters

ValueCountFrequency (%)
0 99770
96.1%
1 4000
 
3.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 103770
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 99770
96.1%
1 4000
 
3.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 103770
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 99770
96.1%
1 4000
 
3.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 103770
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 99770
96.1%
1 4000
 
3.9%

price
Real number (ℝ)

Distinct53
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean28.815537
Minimum5.99
Maximum175.99
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size810.8 KiB
2025-01-14T22:54:11.770317image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/

Quantile statistics

Minimum5.99
5-th percentile6.99
Q111.99
median19.99
Q335.99
95-th percentile87.14
Maximum175.99
Range170
Interquartile range (IQR)24

Descriptive statistics

Standard deviation27.737183
Coefficient of variation (CV)0.96257736
Kurtosis9.3428347
Mean28.815537
Median Absolute Deviation (MAD)10
Skewness2.7033784
Sum2990188.2
Variance769.35132
MonotonicityNot monotonic
2025-01-14T22:54:11.871654image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
19.99 8446
 
8.1%
13.99 5849
 
5.6%
29.99 4527
 
4.4%
9.99 4071
 
3.9%
11.99 4045
 
3.9%
15.99 3761
 
3.6%
23.99 2924
 
2.8%
37.99 2862
 
2.8%
39.99 2726
 
2.6%
8.97 2622
 
2.5%
Other values (43) 61937
59.7%
ValueCountFrequency (%)
5.99 1465
1.4%
6.36 1113
1.1%
6.44 1308
1.3%
6.99 2271
2.2%
7.82 1149
1.1%
7.95 1635
1.6%
7.99 1316
1.3%
8.54 1178
1.1%
8.97 2622
2.5%
8.99 2221
2.1%
ValueCountFrequency (%)
175.99 1255
1.2%
118 1452
1.4%
101 1449
1.4%
87.14 1142
1.1%
79.99 1434
1.4%
74.95 1099
1.1%
59.9 1881
1.8%
57 1292
1.2%
55.96 1517
1.5%
51 1426
1.4%

Day_elapsed
Real number (ℝ)

Distinct1333
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean735.971
Minimum0
Maximum1332
Zeros83
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size810.8 KiB
2025-01-14T22:54:11.983357image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile121
Q1476
median784
Q31024
95-th percentile1191
Maximum1332
Range1332
Interquartile range (IQR)548

Descriptive statistics

Standard deviation339.56109
Coefficient of variation (CV)0.46137835
Kurtosis-0.91646992
Mean735.971
Median Absolute Deviation (MAD)264
Skewness-0.37788496
Sum76371711
Variance115301.73
MonotonicityNot monotonic
2025-01-14T22:54:12.102891image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1167 181
 
0.2%
1164 176
 
0.2%
1159 175
 
0.2%
1157 175
 
0.2%
1177 172
 
0.2%
1183 167
 
0.2%
1166 165
 
0.2%
1171 164
 
0.2%
1160 161
 
0.2%
1175 161
 
0.2%
Other values (1323) 102073
98.4%
ValueCountFrequency (%)
0 83
0.1%
1 12
 
< 0.1%
2 12
 
< 0.1%
3 12
 
< 0.1%
4 11
 
< 0.1%
5 14
 
< 0.1%
6 24
 
< 0.1%
7 20
 
< 0.1%
8 23
 
< 0.1%
9 24
 
< 0.1%
ValueCountFrequency (%)
1332 3
 
< 0.1%
1331 2
 
< 0.1%
1330 11
< 0.1%
1329 7
< 0.1%
1328 4
 
< 0.1%
1327 8
< 0.1%
1326 12
< 0.1%
1325 13
< 0.1%
1324 12
< 0.1%
1323 10
< 0.1%

depth
Real number (ℝ)

High correlation 

Distinct87518
Distinct (%)84.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-53.634878
Minimum-100
Maximum-7.3141478
Zeros0
Zeros (%)0.0%
Negative103770
Negative (%)100.0%
Memory size810.8 KiB
2025-01-14T22:54:12.209794image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/

Quantile statistics

Minimum-100
5-th percentile-81.901228
Q1-64.837411
median-48.350618
Q3-45.146789
95-th percentile-27.176234
Maximum-7.3141478
Range92.685852
Interquartile range (IQR)19.690622

Descriptive statistics

Standard deviation19.226345
Coefficient of variation (CV)-0.35846721
Kurtosis-0.51313102
Mean-53.634878
Median Absolute Deviation (MAD)15.801428
Skewness0.0065849028
Sum-5565691.2
Variance369.65233
MonotonicityNot monotonic
2025-01-14T22:54:12.317511image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-100 1474
 
1.4%
-62.15480079 678
 
0.7%
-80.84890017 669
 
0.6%
-80.84250123 566
 
0.5%
-64.43692464 451
 
0.4%
-81.44470947 417
 
0.4%
-63.13134616 366
 
0.4%
-62.79221066 242
 
0.2%
-64.09818971 216
 
0.2%
-63.51209851 192
 
0.2%
Other values (87508) 98499
94.9%
ValueCountFrequency (%)
-100 1474
1.4%
-83.96139282 8
 
< 0.1%
-83.83256032 13
 
< 0.1%
-83.82081242 1
 
< 0.1%
-83.8174782 23
 
< 0.1%
-83.8085442 6
 
< 0.1%
-83.7836055 2
 
< 0.1%
-83.7780258 25
 
< 0.1%
-83.7650551 3
 
< 0.1%
-83.75760226 12
 
< 0.1%
ValueCountFrequency (%)
-7.314147829 1
< 0.1%
-7.546417695 1
< 0.1%
-7.626836017 1
< 0.1%
-7.855493736 1
< 0.1%
-7.876928883 1
< 0.1%
-7.902762854 1
< 0.1%
-7.982638707 1
< 0.1%
-7.985318326 1
< 0.1%
-7.997865551 1
< 0.1%
-8.004889037 1
< 0.1%

breadth
Real number (ℝ)

High correlation 

Distinct75161
Distinct (%)72.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.0543388
Minimum0.013189577
Maximum3.3429617
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size810.8 KiB
2025-01-14T22:54:12.422280image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/

Quantile statistics

Minimum0.013189577
5-th percentile0.35393519
Q10.57086406
median0.80398825
Q31.3105173
95-th percentile2.8196561
Maximum3.3429617
Range3.3297722
Interquartile range (IQR)0.73965323

Descriptive statistics

Standard deviation0.74659197
Coefficient of variation (CV)0.70811389
Kurtosis1.334139
Mean1.0543388
Median Absolute Deviation (MAD)0.27840792
Skewness1.4814011
Sum109408.74
Variance0.55739957
MonotonicityNot monotonic
2025-01-14T22:54:12.629626image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.8039882472 11876
 
11.4%
0.4217663033 1474
 
1.4%
0.8039882472 1187
 
1.1%
3.229167424 775
 
0.7%
2.326794638 683
 
0.7%
3.342961744 668
 
0.6%
3.155294562 539
 
0.5%
3.153489358 457
 
0.4%
2.731573984 366
 
0.4%
2.696855083 243
 
0.2%
Other values (75151) 85502
82.4%
ValueCountFrequency (%)
0.01318957667 1
< 0.1%
0.02141185931 1
< 0.1%
0.02321670867 1
< 0.1%
0.02377770131 1
< 0.1%
0.02410144519 1
< 0.1%
0.02616735167 1
< 0.1%
0.02738159501 1
< 0.1%
0.03015226037 1
< 0.1%
0.03100424373 1
< 0.1%
0.0313369661 1
< 0.1%
ValueCountFrequency (%)
3.342961744 668
0.6%
3.342834319 1
 
< 0.1%
3.34206396 1
 
< 0.1%
3.34121746 1
 
< 0.1%
3.340538254 1
 
< 0.1%
3.340027091 1
 
< 0.1%
3.339597232 2
 
< 0.1%
3.338871513 1
 
< 0.1%
3.332836022 3
 
< 0.1%
3.331944298 1
 
< 0.1%

Topic_1
Real number (ℝ)

Distinct87499
Distinct (%)84.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.10979924
Minimum4.147535 × 10-20
Maximum0.99720939
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size810.8 KiB
2025-01-14T22:54:12.740856image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/

Quantile statistics

Minimum4.147535 × 10-20
5-th percentile1.2442003 × 10-19
Q12.9256296 × 10-19
median1.3974215 × 10-18
Q30.13854672
95-th percentile0.57675065
Maximum0.99720939
Range0.99720939
Interquartile range (IQR)0.13854672

Descriptive statistics

Standard deviation0.20419943
Coefficient of variation (CV)1.8597526
Kurtosis5.3560048
Mean0.10979924
Median Absolute Deviation (MAD)1.326806 × 10-18
Skewness2.3424148
Sum11393.868
Variance0.041697408
MonotonicityNot monotonic
2025-01-14T22:54:12.849203image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.2 1474
 
1.4%
0.3787096587 682
 
0.7%
7.061552133 × 10-20669
 
0.6%
6.958269283 × 10-20566
 
0.5%
0.9964347246 457
 
0.4%
2.784257975 × 10-19417
 
0.4%
0.9029504554 366
 
0.4%
0.1192807054 243
 
0.2%
4.493223647 × 10-19216
 
0.2%
6.87955492 × 10-20192
 
0.2%
Other values (87489) 98488
94.9%
ValueCountFrequency (%)
4.147535011 × 10-202
 
< 0.1%
4.268259352 × 10-203
 
< 0.1%
4.489099647 × 10-201
 
< 0.1%
4.664085127 × 10-201
 
< 0.1%
4.920291367 × 10-201
 
< 0.1%
4.954693228 × 10-201
 
< 0.1%
4.955025616 × 10-201
 
< 0.1%
4.965180013 × 10-2084
0.1%
4.978253443 × 10-202
 
< 0.1%
5.059042651 × 10-2013
 
< 0.1%
ValueCountFrequency (%)
0.9972093882 13
< 0.1%
0.9969672982 4
 
< 0.1%
0.9969358365 1
 
< 0.1%
0.9969175778 8
< 0.1%
0.9967185579 1
 
< 0.1%
0.996697176 1
 
< 0.1%
0.9966875567 2
 
< 0.1%
0.9966837774 1
 
< 0.1%
0.9966745614 2
 
< 0.1%
0.9966675132 3
 
< 0.1%

Topic_2
Real number (ℝ)

Distinct87450
Distinct (%)84.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.10664088
Minimum4.4834084 × 10-20
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size810.8 KiB
2025-01-14T22:54:12.962628image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/

Quantile statistics

Minimum4.4834084 × 10-20
5-th percentile1.1613703 × 10-19
Q12.7679702 × 10-19
median7.5355331 × 10-19
Q30.097049545
95-th percentile0.6407062
Maximum1
Range1
Interquartile range (IQR)0.097049545

Descriptive statistics

Standard deviation0.21653658
Coefficient of variation (CV)2.0305212
Kurtosis5.6746549
Mean0.10664088
Median Absolute Deviation (MAD)6.3657353 × 10-19
Skewness2.4791827
Sum11066.125
Variance0.04688809
MonotonicityNot monotonic
2025-01-14T22:54:13.071695image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.2 1474
 
1.4%
1 775
 
0.7%
5.796967792 × 10-20678
 
0.7%
6.958269283 × 10-20566
 
0.5%
9.856739732 × 10-20451
 
0.4%
2.784257975 × 10-19417
 
0.4%
0.09704954462 366
 
0.4%
0.8807192946 243
 
0.2%
4.493223647 × 10-19216
 
0.2%
6.87955492 × 10-20192
 
0.2%
Other values (87440) 98392
94.8%
ValueCountFrequency (%)
4.483408352 × 10-204
 
< 0.1%
4.541514264 × 10-2026
< 0.1%
4.569832018 × 10-201
 
< 0.1%
4.657171629 × 10-2053
0.1%
4.87253231 × 10-201
 
< 0.1%
4.955025616 × 10-201
 
< 0.1%
4.958027805 × 10-201
 
< 0.1%
4.966478569 × 10-201
 
< 0.1%
5.032363279 × 10-201
 
< 0.1%
5.059042651 × 10-2013
 
< 0.1%
ValueCountFrequency (%)
1 775
0.7%
0.999949551 1
 
< 0.1%
0.9997966969 1
 
< 0.1%
0.9997416009 1
 
< 0.1%
0.9997369537 1
 
< 0.1%
0.999734747 1
 
< 0.1%
0.9997024913 2
 
< 0.1%
0.9995200362 1
 
< 0.1%
0.9994864076 2
 
< 0.1%
0.9994287136 2
 
< 0.1%

Topic_3
Real number (ℝ)

Distinct87459
Distinct (%)84.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.098552634
Minimum4.9782534 × 10-20
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size810.8 KiB
2025-01-14T22:54:13.187694image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/

Quantile statistics

Minimum4.9782534 × 10-20
5-th percentile1.226766 × 10-19
Q12.784258 × 10-19
median1.4159254 × 10-18
Q30.041665251
95-th percentile0.62129034
Maximum1
Range1
Interquartile range (IQR)0.041665251

Descriptive statistics

Standard deviation0.21334689
Coefficient of variation (CV)2.1648015
Kurtosis5.5699914
Mean0.098552634
Median Absolute Deviation (MAD)1.3353064 × 10-18
Skewness2.4839758
Sum10226.807
Variance0.045516895
MonotonicityNot monotonic
2025-01-14T22:54:13.305534image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.2 1474
 
1.4%
0.6212903413 683
 
0.7%
7.061552133 × 10-20669
 
0.6%
1 668
 
0.6%
0.003565275424 456
 
0.4%
2.784257975 × 10-19417
 
0.4%
1.088934587 × 10-19366
 
0.4%
8.068804389 × 10-20242
 
0.2%
0.2017337698 216
 
0.2%
6.87955492 × 10-20192
 
0.2%
Other values (87449) 98387
94.8%
ValueCountFrequency (%)
4.978253443 × 10-202
 
< 0.1%
5.056807158 × 10-201
 
< 0.1%
5.061066349 × 10-201
 
< 0.1%
5.175948012 × 10-201
 
< 0.1%
5.196888555 × 10-205
< 0.1%
5.309432565 × 10-202
 
< 0.1%
5.316742399 × 10-204
< 0.1%
5.327206717 × 10-203
< 0.1%
5.407800269 × 10-201
 
< 0.1%
5.423471178 × 10-201
 
< 0.1%
ValueCountFrequency (%)
1 668
0.6%
0.9999940273 1
 
< 0.1%
0.9999429137 1
 
< 0.1%
0.9998804142 1
 
< 0.1%
0.9998276128 1
 
< 0.1%
0.9997865755 1
 
< 0.1%
0.9997513249 2
 
< 0.1%
0.9996904585 1
 
< 0.1%
0.9991608211 1
 
< 0.1%
0.999137088 3
 
< 0.1%

Topic_4
Real number (ℝ)

High correlation 

Distinct75430
Distinct (%)72.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.57276361
Minimum4.147535 × 10-20
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size810.8 KiB
2025-01-14T22:54:13.435199image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/

Quantile statistics

Minimum4.147535 × 10-20
5-th percentile1.1794268 × 10-19
Q10.24704324
median0.60354148
Q30.93530256
95-th percentile1
Maximum1
Range1
Interquartile range (IQR)0.68825932

Descriptive statistics

Standard deviation0.35154081
Coefficient of variation (CV)0.61376248
Kurtosis-1.4001522
Mean0.57276361
Median Absolute Deviation (MAD)0.34154322
Skewness-0.22231335
Sum59435.68
Variance0.12358094
MonotonicityNot monotonic
2025-01-14T22:54:13.551078image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 14049
 
13.5%
0.2 1474
 
1.4%
5.796967792 × 10-20678
 
0.7%
7.061552133 × 10-20669
 
0.6%
6.958269283 × 10-20566
 
0.5%
9.856739732 × 10-20451
 
0.4%
1.088934587 × 10-19366
 
0.4%
8.068804389 × 10-20242
 
0.2%
0.7982662302 216
 
0.2%
1 213
 
0.2%
Other values (75420) 84846
81.8%
ValueCountFrequency (%)
4.147535011 × 10-202
 
< 0.1%
4.268259352 × 10-203
 
< 0.1%
4.483408352 × 10-204
 
< 0.1%
4.489099647 × 10-201
 
< 0.1%
4.541514264 × 10-2026
< 0.1%
4.569832018 × 10-201
 
< 0.1%
4.588572266 × 10-201
 
< 0.1%
4.657171629 × 10-2053
0.1%
4.678108418 × 10-201
 
< 0.1%
4.783962815 × 10-201
 
< 0.1%
ValueCountFrequency (%)
1 14049
13.5%
1 213
 
0.2%
1 8
 
< 0.1%
0.9999969657 1
 
< 0.1%
0.9999918825 1
 
< 0.1%
0.9999902135 1
 
< 0.1%
0.9999891108 1
 
< 0.1%
0.9999888429 1
 
< 0.1%
0.9999830744 1
 
< 0.1%
0.9999806559 1
 
< 0.1%

Topic_5
Real number (ℝ)

Distinct87319
Distinct (%)84.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.11224363
Minimum4.6781084 × 10-20
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size810.8 KiB
2025-01-14T22:54:13.657053image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/

Quantile statistics

Minimum4.6781084 × 10-20
5-th percentile1.0889346 × 10-19
Q12.6416798 × 10-19
median7.1008584 × 10-19
Q30.11258138
95-th percentile0.65877124
Maximum1
Range1
Interquartile range (IQR)0.11258138

Descriptive statistics

Standard deviation0.22197813
Coefficient of variation (CV)1.9776458
Kurtosis4.8024302
Mean0.11224363
Median Absolute Deviation (MAD)5.9999214 × 10-19
Skewness2.3269141
Sum11647.521
Variance0.04927429
MonotonicityNot monotonic
2025-01-14T22:54:13.767042image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.2 1474
 
1.4%
5.796967792 × 10-20678
 
0.7%
7.061552133 × 10-20669
 
0.6%
6.958269283 × 10-20566
 
0.5%
1 539
 
0.5%
9.856739732 × 10-20451
 
0.4%
2.784257975 × 10-19417
 
0.4%
1.088934587 × 10-19366
 
0.4%
8.068804389 × 10-20242
 
0.2%
4.493223647 × 10-19216
 
0.2%
Other values (87309) 98152
94.6%
ValueCountFrequency (%)
4.678108418 × 10-201
 
< 0.1%
4.963602213 × 10-207
 
< 0.1%
4.965180013 × 10-2084
0.1%
5.122504142 × 10-209
 
< 0.1%
5.23708597 × 10-203
 
< 0.1%
5.288316653 × 10-207
 
< 0.1%
5.342610105 × 10-201
 
< 0.1%
5.456151839 × 10-201
 
< 0.1%
5.462142388 × 10-201
 
< 0.1%
5.475498772 × 10-201
 
< 0.1%
ValueCountFrequency (%)
1 539
0.5%
0.9999879284 1
 
< 0.1%
0.9999750175 1
 
< 0.1%
0.9999308645 1
 
< 0.1%
0.9999145486 1
 
< 0.1%
0.9998761313 1
 
< 0.1%
0.9998655154 1
 
< 0.1%
0.9998610455 1
 
< 0.1%
0.9998356783 1
 
< 0.1%
0.99981854 1
 
< 0.1%

Interactions

2025-01-14T22:54:06.525568image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
2025-01-14T22:53:53.725605image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
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2025-01-14T22:54:03.082647image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
2025-01-14T22:54:04.182890image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
2025-01-14T22:54:05.251826image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
2025-01-14T22:54:06.439921image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/

Correlations

2025-01-14T22:54:13.866311image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
Average_ratingDay_elapsedHelpfulnessNum_of_RatingRatingTopic_1Topic_2Topic_3Topic_4Topic_5breadthdepthhas_imagesprice
Average_rating1.0000.079-0.0290.2160.1220.014-0.0050.034-0.059-0.0110.0330.0140.080-0.012
Day_elapsed0.0791.000-0.086-0.1480.0370.0420.005-0.012-0.036-0.0350.0230.0250.034-0.014
Helpfulness-0.029-0.0861.000-0.0220.003-0.0160.021-0.0450.105-0.001-0.1330.0200.0300.053
Num_of_Rating0.216-0.148-0.0221.0000.052-0.020-0.0120.102-0.035-0.0310.043-0.0190.032-0.060
Rating0.1220.0370.0030.0521.0000.0920.0550.0770.1650.0660.1370.1260.0200.074
Topic_10.0140.042-0.016-0.0200.0921.0000.146-0.082-0.153-0.118-0.1910.3740.0400.055
Topic_2-0.0050.0050.021-0.0120.0550.1461.000-0.278-0.071-0.156-0.1930.2530.0330.038
Topic_30.034-0.012-0.0450.1020.077-0.082-0.2781.000-0.078-0.050-0.0490.1070.043-0.149
Topic_4-0.059-0.0360.105-0.0350.165-0.153-0.071-0.0781.000-0.028-0.551-0.5230.0520.015
Topic_5-0.011-0.035-0.001-0.0310.066-0.118-0.156-0.050-0.0281.000-0.1780.1640.0510.127
breadth0.0330.023-0.1330.0430.137-0.191-0.193-0.049-0.551-0.1781.000-0.1050.058-0.043
depth0.0140.0250.020-0.0190.1260.3740.2530.107-0.5230.164-0.1051.0000.0530.029
has_images0.0800.0340.0300.0320.0200.0400.0330.0430.0520.0510.0580.0531.0000.077
price-0.012-0.0140.053-0.0600.0740.0550.038-0.1490.0150.127-0.0430.0290.0771.000

Missing values

2025-01-14T22:54:07.657655image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
A simple visualization of nullity by column.
2025-01-14T22:54:07.922286image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2025-01-14T22:54:08.174193image/svg+xmlMatplotlib v3.7.0, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

product_nameAverage_ratingNum_of_RatingRatingreview_titleReview_TextPosted_DateHelpfulnesshas_imagespriceDay_elapseddepthbreadthTopic_1Topic_2Topic_3Topic_4Topic_5
0Panasonic Portable AM / FM Radio, Battery Operated Analog Radio, AC Powered, Silver (RF-2400D) 22.8 x 7.8 x 10.84.6276185.0It's a good productThis radio was perfect for my father. He's older (in his 80s) and he wanted a simple transistor radio for the bathroom that runs on batteries. He didn't want anything too fancy or expensive. This fits the bill.2022-04-210034.95348-64.6551710.6692664.020516e-194.020516e-193.713893e-020.9628614.020516e-19
1Panasonic Portable AM / FM Radio, Battery Operated Analog Radio, AC Powered, Silver (RF-2400D) 22.8 x 7.8 x 10.84.6276181.0nothing came in?I couldn't get any stations in , worthless to me. YouTube videos why I bought it{: buyer beware!2022-08-290034.95218-82.0118580.8039881.027679e-181.027679e-181.027679e-181.0000001.027679e-18
2Panasonic Portable AM / FM Radio, Battery Operated Analog Radio, AC Powered, Silver (RF-2400D) 22.8 x 7.8 x 10.84.6276183.0Great for basement or garage use.This affordable radio is perfect for my needs. Yet, I miss the quality from the higher end Sony portable. Sorry, the sound is a bit tinny. Yet, I am a fan of the controls, display and design. Good value.2021-07-161034.95627-29.5752721.0791582.837599e-025.696896e-018.302376e-030.3936322.111245e-19
3Panasonic Portable AM / FM Radio, Battery Operated Analog Radio, AC Powered, Silver (RF-2400D) 22.8 x 7.8 x 10.84.6276185.0PROS/CONS Good things come in SMALL packages!PROS and CONS and why I chose this one. The story:My mother still lives in independent living with her older sister (she's turning 90, her sister 92).She couldn't get visitors for her birthday because all independent and assisted living places are on lockdown with what's going on.SO I had to find something EASY for her to set up on her own, that was small for her bedside table, and would be a good-sounding radio. EUREKA!PROS:PACKAGING - I was concerned re how it would arrive, but my mother said it was in heavy foam packaging. Came in perfect condition.SIZE - PERFECT SMALL RADIO for her night stand. MUCH smaller than the 22 inch dimensions it shows in top description! It's small enough for a SMALL nightstand.SET UP - MY mother had no problem setting it up or figuring out knobs. This is as easy as radios from the '60's. Basically a couple knobs and a switch to go back and forth between AM and FMSOUND - I was on the phone with my mother as she dialed through various stations and GREAT sound. She was delighted and said, HEAR THIS!PRICE - CAN'T BEAT THE PRICE!2020-04-080034.951091-10.5684440.4559521.146106e-011.800103e-019.582888e-030.3364063.593906e-01
4Panasonic Portable AM / FM Radio, Battery Operated Analog Radio, AC Powered, Silver (RF-2400D) 22.8 x 7.8 x 10.84.6276181.0Doesn’t pick up wellWaste of money,,,,, can’t get stations on this radio as clear as others2020-12-250034.95830-48.5894760.5112441.724329e-028.199283e-027.909718e-190.9007647.909718e-19
5Panasonic Portable AM / FM Radio, Battery Operated Analog Radio, AC Powered, Silver (RF-2400D) 22.8 x 7.8 x 10.84.6276185.0Surprise!Surprisingly wonderful little radio. Just what we wanted!!2020-04-100034.951089-65.2816530.7461424.479609e-194.479609e-191.060368e-020.9893964.479609e-19
6Panasonic Portable AM / FM Radio, Battery Operated Analog Radio, AC Powered, Silver (RF-2400D) 22.8 x 7.8 x 10.84.6276184.0Fair to good receptionVery good portable radio. Great size. Fair to good reception in a difficult reception area.I have tried more expensive radios that didpoorly.2020-05-230034.951046-29.1126281.9127621.913648e-017.258351e-011.743831e-190.0760456.754892e-03
7Panasonic Portable AM / FM Radio, Battery Operated Analog Radio, AC Powered, Silver (RF-2400D) 22.8 x 7.8 x 10.84.6276184.0Cute LITTLE thing. For local stations only.Works great for background music and local news in home office.Pros:-AC (electric cord) or 4 AA batteries.-VERY portable—it’s small. See photos.-Very simple to use.-Easy to read numbers.-Throwback classic radio look.-Sound from the one speaker is clear — if the station comes in.Cons:-Pulls in local stations (very local) but not half as many as your car radio (those are built to a very robust standard). If your stations are 25+ miles away, you probably won’t get them unless they have a powerful transmitter or you’re in a very good spot for reception.-Just basic mono sound but you shouldn’t be buying this for sound quality anyway.-You might expect something bigger for $292021-03-130134.95752-9.5190010.1232559.594204e-021.900608e-011.275434e-010.3947771.916768e-01
8Panasonic Portable AM / FM Radio, Battery Operated Analog Radio, AC Powered, Silver (RF-2400D) 22.8 x 7.8 x 10.84.6276185.0good purchase!I really like this radio!2021-12-110034.95479-48.4911110.6821043.204450e-191.666134e-026.525723e-030.9768133.204450e-19
9Panasonic Portable AM / FM Radio, Battery Operated Analog Radio, AC Powered, Silver (RF-2400D) 22.8 x 7.8 x 10.84.6276185.0Exactly as picturedDoesn't use much power, perfect for camping, brings in lots of stations.2021-05-040034.95700-46.6103950.6551322.959141e-192.959141e-192.811365e-020.5864473.854396e-01
product_nameAverage_ratingNum_of_RatingRatingreview_titleReview_TextPosted_DateHelpfulnesshas_imagespriceDay_elapseddepthbreadthTopic_1Topic_2Topic_3Topic_4Topic_5
103760Fintie Case for iPad 9.7 2018 2017 / iPad Air 2 / iPad Air 1 - [Corner Protection] Multi-Angle Viewing Folio Cover w/Pocket, Auto Wake/Sleep for iPad 6th / 5th Generation, Ocean Marble4.6434305.0awesome covering ,love that i can prop it up for versatility of use .nothing2020-12-310019.99823-100.0000000.4217662.000000e-012.000000e-012.000000e-012.000000e-012.000000e-01
103761Fintie Case for iPad 9.7 2018 2017 / iPad Air 2 / iPad Air 1 - [Corner Protection] Multi-Angle Viewing Folio Cover w/Pocket, Auto Wake/Sleep for iPad 6th / 5th Generation, Ocean Marble4.6434305.0Love itiPad air2022-08-110019.99235-65.5124430.6552391.170797e-181.170797e-184.406475e-029.559353e-011.170797e-18
103762Fintie Case for iPad 9.7 2018 2017 / iPad Air 2 / iPad Air 1 - [Corner Protection] Multi-Angle Viewing Folio Cover w/Pocket, Auto Wake/Sleep for iPad 6th / 5th Generation, Ocean Marble4.6434305.0BeautifulI am pleased with this iPad cover. It is bulkier than I wanted, but I am overall pleased.2020-11-030019.99881-51.1773800.7544118.626995e-046.667965e-039.505683e-199.924693e-019.505683e-19
103763Fintie Case for iPad 9.7 2018 2017 / iPad Air 2 / iPad Air 1 - [Corner Protection] Multi-Angle Viewing Folio Cover w/Pocket, Auto Wake/Sleep for iPad 6th / 5th Generation, Ocean Marble4.6434305.0Love!Love this cover. Great quality love the pocket too!2023-03-240019.9910-45.6471930.6435984.001619e-017.196841e-021.889583e-195.278697e-011.889583e-19
103764Fintie Case for iPad 9.7 2018 2017 / iPad Air 2 / iPad Air 1 - [Corner Protection] Multi-Angle Viewing Folio Cover w/Pocket, Auto Wake/Sleep for iPad 6th / 5th Generation, Ocean Marble4.6434304.0I love it!Cover for my iPad. Love the color2021-08-310019.99580-81.6455940.8039884.421745e-194.421745e-194.421745e-191.000000e+004.421745e-19
103765Fintie Case for iPad 9.7 2018 2017 / iPad Air 2 / iPad Air 1 - [Corner Protection] Multi-Angle Viewing Folio Cover w/Pocket, Auto Wake/Sleep for iPad 6th / 5th Generation, Ocean Marble4.6434305.0Great iPad cover at an economical price!It’s very sturdy & protective! Easy to position for free standing.2022-01-230019.99435-48.8235773.0847262.333927e-035.245237e-032.007745e-192.007745e-199.924208e-01
103766Fintie Case for iPad 9.7 2018 2017 / iPad Air 2 / iPad Air 1 - [Corner Protection] Multi-Angle Viewing Folio Cover w/Pocket, Auto Wake/Sleep for iPad 6th / 5th Generation, Ocean Marble4.6434305.0Best iPad caseNothing to dislike. Excellent quality, easy to use and good price.2022-06-170019.99290-26.6638661.5821802.705334e-024.373206e-016.482005e-206.939895e-024.662271e-01
103767Fintie Case for iPad 9.7 2018 2017 / iPad Air 2 / iPad Air 1 - [Corner Protection] Multi-Angle Viewing Folio Cover w/Pocket, Auto Wake/Sleep for iPad 6th / 5th Generation, Ocean Marble4.6434305.0Durable cover for iPad!Love this product. Color is pretty.Easy to hold and prop up.Uses: reading books, playing games, Searching internet.2021-03-010019.99763-28.2924490.9341429.884520e-027.816330e-022.179336e-192.685606e-015.544309e-01
103768Fintie Case for iPad 9.7 2018 2017 / iPad Air 2 / iPad Air 1 - [Corner Protection] Multi-Angle Viewing Folio Cover w/Pocket, Auto Wake/Sleep for iPad 6th / 5th Generation, Ocean Marble4.6434305.0Worth itQuick shipping. Fits ipad easily. Nice colors.2021-01-190019.99804-32.8630610.4839442.226626e-022.076929e-036.867447e-199.026192e-017.303760e-02
103769Fintie Case for iPad 9.7 2018 2017 / iPad Air 2 / iPad Air 1 - [Corner Protection] Multi-Angle Viewing Folio Cover w/Pocket, Auto Wake/Sleep for iPad 6th / 5th Generation, Ocean Marble4.6434305.0Great!Sturdy, easy to hold and maneuver, durable2020-06-250019.991012-30.7538052.7637874.969548e-031.117813e-021.722669e-192.927559e-029.545767e-01

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202Cable Clips Management - Nightstand Accessories - Cord Organizer - Desk Cable Management - Wire Holder System - Adhesive Cord Clips - Home, Office, Cubicle, Car - Gift Idea - Black4.3209025.0Easy to useThis product adheres, to any surface type and stays. Just peel the back paper of a press into the area you wish yo gave it. It can hold different size cables2020-10-06008.97912-46.7797010.3542311.762403e-011.027677e-014.284148e-197.209920e-014.284148e-194
453PROZOR 192KHz Digital to Analog Audio Converter DAC Digital SPDIF Optical to Analog L/R RCA Converter Toslink Optical to 3.5mm Jack Adapter for PS3 HD DVD PS4 Amp Apple TV Home Cinema4.4365375.0Works Perfectly; Easy InstallWorked as advertised. Couldn't be easier to install.2021-10-250013.85553-29.4917721.5516561.916472e-022.753437e-197.108954e-021.885149e-017.212308e-014
575Upgraded, Anker Soundcore Boost Bluetooth Speaker with Well-Balanced Sound, BassUp, 12H Playtime, USB-C, IPX7 Waterproof, Wireless Speaker with Customizable EQ via App, Wireless Stereo Pairing4.6286652.0Good sound, terrible battery performance.Good sound for a speaker this size. However, the battery life is abysmal. After about six months, the batter started dying really quickly. At this point, it won’t even hold a charge. Save your money or get a different brand.2021-03-0900101.00889-63.2034890.8652121.980023e-194.320803e-011.980023e-195.679197e-011.980023e-194
583Upgraded, Anker Soundcore Boost Bluetooth Speaker with Well-Balanced Sound, BassUp, 12H Playtime, USB-C, IPX7 Waterproof, Wireless Speaker with Customizable EQ via App, Wireless Stereo Pairing4.6286655.0Nice and loudTakes a while to charge but once charged it lasts for a long time2020-11-1000101.001008-81.8677760.8039887.375232e-197.375232e-197.375232e-191.000000e+007.375232e-194
601amFilm Screen Protector for iPad Mini 5/iPad Mini 4, Tempered Glass, 1 Pack4.6198475.0Customer ServiceI had an issue with the first one received, contacted customer service and they sent a new one no charge. I haveput it on my Ipad mini and I love it. It was so easy to do.2020-02-05006.361284-63.3533591.1088852.362201e-192.362201e-192.362201e-194.483169e-015.516831e-014
632iFixit Pro Tech Toolkit - Electronics, Smartphone, Computer & Tablet Repair Kit4.9173185.0quality productVery good quality, worth the money2022-04-020074.95509-63.0609692.1782301.262107e-198.340242e-011.262107e-191.659758e-011.262107e-194